90 research outputs found
Design and Implementation of Secure Chaotic Communication Systems
Chaotic systems have properties such as ergodicity, sensitivity to initial conditions/parameter mismatches, mixing property, deterministic dynamics, structure complexity, to mention a few, that map nicely with cryptographic requirements such as confusion, diffusion, deterministic pseudorandomness, algorithm complexity. Furthermore, the possibility of chaotic synchronization, where the master system (transmitter) is driving the slave system (receiver) by its output signal, made it probable for the possible utilization of chaotic systems to implement security in the communication systems. Many methods like chaotic masking, chaotic modulation, inclusion, chaotic shift keying (CSK) had been proposed however, many attack methods later showed them to be insecure. Different modifications of these methods also exist in the literature to improve the security, but almost all suffer from the same drawback. Therefore, the implementation of chaotic systems in security still remains a challenge. In this work, different possibilities on how it might be possible to improve the security of the existing methods are explored. The main problem with the existing methods is that the message imprint could be found in the dynamics of the transmitted signal, therefore by some signal processing or pattern classification techniques, etc, allow the exposition of the hidden message. Therefore, the challenge is to remove any pattern or change in dynamics that the message might bring in the transmitted signal
Synchronization of Different Fractional Order Time-Delay Chaotic Systems Using Active Control
Chaos synchronization of different fractional order time-delay chaotic systems is considered. Based on the Laplace transform theory, the conditions for achieving synchronization of different fractional order time-delay chaotic systems are analyzed by use of active control technique. Then numerical simulations are provided to verify the effectiveness and feasibility of the developed method. At last, effects of the fraction order and the time delay on synchronization are further researched
Design and implementation of secure chaotic communication systems
Chaotic systems have properties such as ergodicity, sensitivity to initial conditions/parameter mismatches, mixing property, deterministic dynamics, structure complexity, to mention a few, that map nicely with cryptographic requirements such as confusion, diffusion, deterministic pseudorandomness, algorithm complexity. Furthermore, the possibility of chaotic synchronization, where the master system (transmitter) is driving the slave system (receiver) by its output signal, made it probable for the possible utilization of chaotic systems to implement security in the communication systems. Many methods like chaotic masking, chaotic modulation, inclusion, chaotic shift keying (CSK) had been proposed however, many attack methods later showed them to be insecure. Different modifications of these methods also exist in the literature to improve the security, but almost all suffer from the same drawback. Therefore, the implementation of chaotic systems in security still remains a challenge. In this work, different possibilities on how it might be possible to improve the security of the existing methods are explored. The main problem with the existing methods is that the message imprint could be found in the dynamics of the transmitted signal, therefore by some signal processing or pattern classification techniques, etc, allow the exposition of the hidden message. Therefore, the challenge is to remove any pattern or change in dynamics that the message might bring in the transmitted signal.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings
Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I
Table of Contents ........................ Page III
Symposium Committees .............. Page IV
Special Thanks ............................. Page V
Conference program (incl. page numbers of papers)
................... Page VI
Conference papers
Invited talks ................................ Page 1
Regular Papers ........................... Page 14
Wednesday, May 26th, 2010 ......... Page 15
Thursday, May 27th, 2010 .......... Page 110
Friday, May 28th, 2010 ............... Page 210
Author index ............................... Page XII
Stochastic analysis of nonlinear dynamics and feedback control for gene regulatory networks with applications to synthetic biology
The focus of the thesis is the investigation of the generalized repressilator model
(repressing genes ordered in a ring structure). Using nonlinear bifurcation analysis
stable and quasi-stable periodic orbits in this genetic network are characterized
and a design for a switchable and controllable genetic oscillator is proposed. The
oscillator operates around a quasi-stable periodic orbit using the classical engineering
idea of read-out based control. Previous genetic oscillators have been
designed around stable periodic orbits, however we explore the possibility of
quasi-stable periodic orbit expecting better controllability.
The ring topology of the generalized repressilator model has spatio-temporal
symmetries that can be understood as propagating perturbations in discrete lattices.
Network topology is a universal cross-discipline transferable concept and
based on it analytical conditions for the emergence of stable and quasi-stable
periodic orbits are derived. Also the length and distribution of quasi-stable oscillations
are obtained. The findings suggest that long-lived transient dynamics
due to feedback loops can dominate gene network dynamics.
Taking the stochastic nature of gene expression into account a master equation
for the generalized repressilator is derived. The stochasticity is shown to influence
the onset of bifurcations and quality of oscillations. Internal noise is shown to
have an overall stabilizing effect on the oscillating transients emerging from the
quasi-stable periodic orbits.
The insights from the read-out based control scheme for the genetic oscillator
lead us to the idea to implement an algorithmic controller, which would direct
any genetic circuit to a desired state. The algorithm operates model-free, i.e. in
principle it is applicable to any genetic network and the input information is a
data matrix of measured time series from the network dynamics. The application
areas for readout-based control in genetic networks range from classical tissue
engineering to stem cells specification, whenever a quantitatively and temporarily
targeted intervention is required
Study of Climate Variability Patterns at Different Scales – A Complex Network Approach
Das Klimasystem der Erde besteht aus zahlreichen interagierenden Teilsystemen, die sich über verschiedene Zeitskalen hinweg verändern, was zu einer äußerst komplizierten räumlich-zeitlichen Klimavariabilität führt. Das Verständnis von Prozessen, die auf verschiedenen räumlichen und zeitlichen Skalen ablaufen, ist ein entscheidender Aspekt bei der numerischen Wettervorhersage. Die Variabilität des Klimas, ein sich selbst konstituierendes System, scheint in Mustern auf großen Skalen organisiert zu sein. Die Verwendung von Klimanetzwerken hat sich als erfolgreicher Ansatz für die Erkennung der räumlichen Ausbreitung dieser großräumigen Muster in der Variabilität des Klimasystems erwiesen.
In dieser Arbeit wird mit Hilfe von Klimanetzwerken gezeigt, dass die Klimavariabilität nicht nur auf größeren Skalen (Asiatischer Sommermonsun, El Niño/Southern Oscillation), sondern auch auf kleineren Skalen, z.B. auf Wetterzeitskalen, in Mustern organisiert ist. Dies findet Anwendung bei der Erkennung einzelner tropischer Wirbelstürme, bei der Charakterisierung binärer Wirbelsturm-Interaktionen, die zu einer vollständigen Verschmelzung führen, und bei der Untersuchung der intrasaisonalen und interannuellen Variabilität des Asiatischen Sommermonsuns.
Schließlich wird die Anwendbarkeit von Klimanetzwerken zur Analyse von Vorhersagefehlern demonstriert, was für die Verbesserung von Vorhersagen von immenser Bedeutung ist. Da korrelierte Fehler durch vorhersagbare Beziehungen zwischen Fehlern verschiedener Regionen aufgrund von zugrunde liegenden systematischen oder zufälligen Prozessen auftreten können, wird gezeigt, dass Fehler-Netzwerke helfen können, die räumlich kohärenten Strukturen von Vorhersagefehlern zu untersuchen. Die Analyse der Fehler-Netzwerk-Topologie von Klimavariablen liefert ein erstes Verständnis der vorherrschenden Fehlerquelle und veranschaulicht das Potenzial von Klimanetzwerken als vielversprechendes Diagnoseinstrument zur Untersuchung von Fehlerkorrelationen.The Earth’s climate system consists of numerous interacting subsystems varying over a multitude of time scales giving rise to highly complicated spatio-temporal climate variability. Understanding processes occurring at different scales, both spatial and temporal, has been a very crucial problem in numerical weather prediction. The variability of climate, a self-constituting system, appears to be organized in patterns on large scales. The climate networks approach has been very successful in detecting the spatial propagation of these large scale patterns of variability in the climate system.
In this thesis, it is demonstrated using climate network approach that climate variability is organized in patterns not only at larger scales (Asian Summer Monsoon, El Niño-Southern Oscillation) but also at shorter scales, e.g., weather time scales. This finds application in detecting individual tropical cyclones, characterizing binary cyclone interaction leading to a complete merger, and studying the intraseasonal and interannual variability of the Asian Summer Monsoon.
Finally, the applicability of the climate network framework to understand forecast error properties is demonstrated, which is crucial for improvement of forecasts. As correlated errors can arise due to the presence of a predictable relationship between errors of different regions because of some underlying systematic or random process, it is shown that error networks can help to analyze the spatially coherent structures of forecast errors. The analysis of the error network topology of a climate variable provides a preliminary understanding of the dominant source of error, which shows the potential of climate networks as a very promising diagnostic tool to study error correlations
Magnetoencephalography
This is a practical book on MEG that covers a wide range of topics. The book begins with a series of reviews on the use of MEG for clinical applications, the study of cognitive functions in various diseases, and one chapter focusing specifically on studies of memory with MEG. There are sections with chapters that describe source localization issues, the use of beamformers and dipole source methods, as well as phase-based analyses, and a step-by-step guide to using dipoles for epilepsy spike analyses. The book ends with a section describing new innovations in MEG systems, namely an on-line real-time MEG data acquisition system, novel applications for MEG research, and a proposal for a helium re-circulation system. With such breadth of topics, there will be a chapter that is of interest to every MEG researcher or clinician
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